一种基于模糊类比的隐性知识获取方法

A. Inoue, S. Tano, T. Iwatani, W. Okamoto, R. Fujioka
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引用次数: 4

摘要

简要介绍了一种利用模糊类比在若干给定情况下获取隐性知识的方法,即模糊类比学习。该方法是作为自然语言交流系统(模糊语言系统)的学习特征提出的,旨在模仿人类学习的观察特征和基于经验的问题解决。本文描述了进一步研究FAL的学习和问题解决的认知模型,以及证明该方法有效性的原型实现,以及计算模型的正式描述
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An acquisition method of implicit knowledge using fuzzy analogy
A method to acquire implicit knowledge among several given cases using fuzzy analogy, called fuzzy analogical learning (FAL), is briefly described. This method is proposed as a learning feature in a natural language communication system, a fuzzy lingual system, which aims to emulate the observational features of human learning and problem solvings based on experiences. Cognitive models of learning and problem solvings for the further study of FAL and a prototype implementation for demonstrating the validity of the method are described as well as a formal description of the computational model.<>
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